The Effect of Wind-Turbine Wakes on Summertime US Midwest Atmospheric Wind Profiles as Observed with Ground-Based Doppler Lidar

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• 作者：Michael E. Rhodes ; Julie K. Lundquist
• 关键词：Diurnal cycle ; Turbine wakes ; Wind energy ; Wind profiles ; Lidar
• 刊名：Boundary-Layer Meteorology
• 出版年：2013
• 出版时间：October 2013
• 年：2013
• 卷：149
• 期：1
• 页码：85-103
• 全文大小：1126KB
• 参考文献：1. Aitken ML, Rhodes ME, Lundquist JK (2012) Performance of a wind-profiling lidar in the region of wind turbine rotor disks. J Atmos Ocean Technol 29:347-55 CrossRef
  2. Baidya Roy S (2011) Simulating impacts of wind farms on local hydrometeorology. J Wind Eng Ind Aerodyn 99:491-98 CrossRef
  3. Baker RW, Walker SN (1984) Wake measurements behind a large horizontal axis wind turbine generator. Sol Energy 33:5-2 CrossRef
  4. Banta RM, Newsom RK, Lundquist JK, Pichugina YL, Coulter RL, Mahrt L (2002) Nocturnal low-level jet characteristics over Kansas during CASES-99. Boundary-Layer Meteorol 105(2):221-52
  5. Barthelmie RJ, Folkerts L, Ormel FT, Sanderhoff P, Eecen PJ, Stobbe O, Nielsen NM (2003) Offshore wind turbine wakes measured by SODAR. J Atmos Ocean Technol 20:466-77 CrossRef
  6. Barthelmie RJ, Frandsen ST, Nielsen MN, Pryor SC, Rethore P-E, J?rgensen HE (2007) Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm. Wind Energy 10:517-28 CrossRef
  7. Barthelmie RJ, Pryor SC, Frandsen ST, Hansen KS, Schepers JG, Rados K, Schlez W, Neubert A, Jensen LE, Neckelmann S (2010) Quantifying the impact of wind turbine wakes on power output at offshore wind farms. J Atmos Ocean Technol 27:1302-317 CrossRef
  8. Bing?l F, Mann J, Foussekis D (2008) Modeling conically scanning lidar error in complex terrain with WAsP engineering. Danmarks Tekniske Universitet, Ris? Nationallaboratoriet for B?redygtig Energi, 2008. 16 pp (Denmark. Forskningscenter Risoe. Risoe-R; No. 1664(EN)). http://orbit.dtu.dk/services/downloadRegister/3332817/ris-r-1664.pdf
  9. Blackadar AK (1957) Boundary layer wind maxima and their significance for the growth of nocturnal inversions. Bull Am Meteorol Soc 38:283-90
  10. Brower M (2012) Wind resource assessment. Wiley, New York CrossRef
  11. Cal RB, Lebrón J, Castillo L, Kang HS, Meneveau C (2010) Experimental study of the horizontally averaged flow structure in a model wind-turbine array boundary layer. J Renew Sustain Energy 2:013106-- 013106-25
  12. Cariou N, Wagner R, Gottschall J (2010) Analysis of vertical wind direction and speed gradients for data from the Met. Mast at H?vs?re. Danmarks Tekniske Universitet, Ris? Nationallaboratoriet for B?redygtig Energi. 34 pp. http://www.risoe.dk/en/Knowledge_base/publications/Reports/ris-r-1733.aspx?sc_lang=da
  13. Chamorro LP, Porté-Agel F (2009) A wind-tunnel investigation of wind-turbine wakes: boundary-layer turbulence effects. Boundary-Layer Meteorol 132:129-49 CrossRef
  14. Chamorro LP, Porté-Agel F (2010) Effects of thermal stability and incoming boundary-layer flow characteristics on wind-turbine wakes: a wind-tunnel study. Boundary-Layer Meteorol 136:515-33 CrossRef
  15. Churchfield MJ, Lee S, Michalakes J, Moriarty PJ (2012) A numerical study of the effects of atmospheric and wake turbulence on wind turbine dynamics. J Turbul 13:1-2 CrossRef
  16. Courtney M, Wagner R, Lindel?w P (2008) Testing and comparison of lidars for profile and turbulence measurements in wind energy. IOP Conf Ser Earth Environ Sci 1:012021. doi:10.1088/1755-1315/1/1/012021
  17. Elliott DL, Barnard JC (1990) Observations of wind turbine wakes and surface roughness effects on wind flow variability. Sol Energy 45:265-83 CrossRef
  18. Fitch A, Lundquist JK, Olson JB (2013) Mesoscale influences of wind farms throughout a diurnal cycle. Mon Weather Rev (in press). doi:10.1175/MWR-D-12-00185.1
  19. Frandsen ST (2007) Turbulence and turbulence-generated structural loading in wind turbine clusters. 135 pp. http://www.risoe.dtu.dk/rispubl/VEA/veapdf/ris-r-1188.pdf
  20. Frehlich R, Meillier Y, Jensen ML, Balsley B (2003) Turbulence measurements with the CIRES tethered lifting system during CASES-99: calibration and spectral analysis of temperature and velocity. J Atmos Sci 60:2487-495 CrossRef
  21. Friedrich K, Lundquist JK, Aitken M, Kalina EA, Marshall RF (2012) Stability and turbulence in the atmospheric boundary layer: a comparison of remote sensing and tower observations. Geophys Res Lett 39:1- CrossRef
  22. Helmis CG, Papadopoulos KH, Asimakopoulos DN, Papageorgas PG, Soilemes AT (1995) An experimental study of the near-wake structure of a wind turbine operating over complex terrain. Sol Energy 54:413-28 CrossRef
  23. Hirth BD, Schroeder JL (2013) Documenting wind speed and power deficits behind a utility-scale wind turbine. J Appl Meteorol Climatol 52:39-6. doi:10.1175/JAMC-D-12-0145.1 CrossRef
  24. Hogstr?m DA, Kambezidis H, Helmis C, Smedman A (1988) A field study of the wake behind a 2 MW wind turbine. Atmos Environ 22:803-20 CrossRef
  25. Iungo GV, Wu Y-T, Porté-Agel F (2013) Field measurements of wind turbine wakes with lidars. J Atmos Ocean Technol 30:274-87. doi:10.1175/JTECH-D-12-00051.1 CrossRef
  26. Jacobson MZ, Delucchi MA (2011) Providing all global energy with wind, water, and solar power, part I: technologies, energy resources, quantities and areas of infrastructure, and materials. Energy Policy 39:1154-169 CrossRef
  27. Kambezidis HD, Asimakopoulos DN, Helmis CG (1990) Wake measurements behind a horizontal-axis 50 kW wind turbine. Sol Wind Technol 7:177-84 CrossRef
  28. K?sler Y, Rahm S, Simmet R, Kühn M (2010) Wake measurements of a multi-MW wind turbine with coherent long-range pulsed doppler wind lidar. J Atmos Ocean Technol 27:1529-532 CrossRef
  29. Kocer G, Mansour M, Chokani N, Abhari RS, Muller M (2011) Full-scale wind turbine near-wake measurements using an instrumented uninhabited aerial vehicle. J Sol Energy Eng 133:041011--041011-8
  30. Magnusson M, Smedman AS (1994) Influence of atmospheric stability on wind turbine wakes. Wind Eng 18:139-51
  31. Mahrt L (1998) Flux sampling errors for aircraft and towers. J Atmos Ocean Technol 15:416-29. doi:10.1175/1520-0426(1998)0150416:FSEFAA2.0.CO;2 CrossRef
  32. Milligan M, Lew D, Corbus D, Piwko R, Miller N, Clark K, Jordan G, Freeman L, Zavadil B, Schuerger M (2009) Large-scale wind integration studies in the United States: preliminary results. NREL/CP-550- 46527, 8 pp
  33. Porte-Agel F, Wu Y-T, Lu H, Conzemius R (2011) Large-eddy simulation of atmospheric boundary layer flow through wind turbines and wind farms. J Wind Eng Ind Aerodyn 99:154-68 CrossRef
  34. Rajewski DA et al (2013) Crop wind energy experiment (CWEX): observations of surface-layer, boundary layer, and mesoscale interactions with a wind farm. Bull Am Meteorol Soc 94:655-72 CrossRef
  35. Sathe A, Mann J, Gottschall J, Courtney MS (2011) Can wind lidars measure turbulence? J Atmos Ocean Technol 28:853-68 CrossRef
  36. Schwartz MN, Elliott DL (2006) Wind shear characteristics at central plains tall towers. National Renewable Energy Laboratory, 13 pp
  37. Smalikho IN, Banakh VA, Pichugina YL, Brewer WA, Banta RM, Lundquist JK, Kelley ND (2013) Lidar investigation of atmosphere effect on a wind turbine wake. J Atmos Ocean Technol. doi:10.1175/JTECH-D-12-00108.1
  38. Stull RB (1988) An introduction to boundary-layer meteorology. Kluwer, Dordrecht, 666 pp
  39. Trujillo J-J, Bing?l F, Larsen GC, Mann J, Kühn M (2011) Light detection and ranging measurements of wake dynamics. Part II: Two-dimensional scanning. Wind Energy 14:61-5 CrossRef
  40. USDA (2012) US county crop harvest. http://www.nass.usda.gov/Charts_and_Maps/Crops_County/index.asp
  41. Walter K, Weiss CC, Swift AHP, Chapman J, Kelley ND (2009) Speed and direction shear in the stable nocturnal boundary layer. J Sol Energy Eng 131:011013--011013-7
  42. Wharton S, Lundquist JK (2012a) Atmospheric stability affects wind turbine power collection. Environ Res Lett 7:014005--014005-9
  43. Wharton S, Lundquist JK (2012b) Assessing atmospheric stability and its impacts on rotor-disk wind characteristics at an onshore wind farm. Wind Energy 15:525-46 CrossRef
  44. Whiteman CD, Bian X, Zhong S (1997) Low-level jet climatology from enhanced rawindsonde observations at a site in the southern Great Plains. J Appl Meteorol 36:1363-376
  45. Wu Y-T, Porté-Agel F (2011) Large-eddy simulation of wind-turbine wakes: evaluation of turbine parametrisations. Boundary-Layer Meteorol 138:345-66 CrossRef
  46. Zhou L, Tian Y, Roy SB, Thorncroft C, Bosart LF, Hu Y (2012) Impacts of wind farms on land surface temperature. Nat Clim Chang 2:539-43
  
• 作者单位：Michael E. Rhodes (1)
  Julie K. Lundquist (1) (2)
  
  1. Department of Atmospheric and Oceanic Sciences, 311 UCB, University of Colorado, Boulder, CO, 80309-0311, USA
  2. National Renewable Energy Laboratory, Golden, CO, 80401, USA
  
• ISSN：1573-1472

文摘

We examine the influence of a modern multi-megawatt wind turbine on wind and turbulence profiles three rotor diameters ( $D$ ) downwind of the turbine. Light detection and ranging (lidar) wind-profile observations were collected during summer 2011 in an operating wind farm in central Iowa at 20-m vertical intervals from 40 to 220 m above the surface. After a calibration period during which two lidars were operated next to each other, one lidar was located approximately $2D$ directly south of a wind turbine; the other lidar was moved approximately $3D$ north of the same wind turbine. Data from the two lidars during southerly flow conditions enabled the simultaneous capture of inflow and wake conditions. The inflow wind and turbulence profiles exhibit strong variability with atmospheric stability: daytime profiles are well-mixed with little shear and strong turbulence, while nighttime profiles exhibit minimal turbulence and considerable shear across the rotor disk region and above. Consistent with the observations available from other studies and with wind-tunnel and large-eddy simulation studies, measurable reductions in wake wind-speeds occur at heights spanning the wind turbine rotor (43-17 m), and turbulent quantities increase in the wake. In generalizing these results as a function of inflow wind speed, we find the wind-speed deficit in the wake is largest at hub height or just above, and the maximum deficit occurs when wind speeds are below the rated speed for the turbine. Similarly, the maximum enhancement of turbulence kinetic energy and turbulence intensity occurs at hub height, although observations at the top of the rotor disk do not allow assessment of turbulence in that region. The wind shear below turbine hub height (quantified here with the power-law coefficient) is found to be a useful parameter to identify whether a downwind lidar observes turbine wake or free-flow conditions. These field observations provide data for validating turbine-wake models and wind-tunnel observations, and for guiding assessments of the impacts of wakes on surface turbulent fluxes or surface temperatures downwind of turbines.